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Data quality assessment in emergency medical services: an objective approach

BACKGROUND: In emergency medical services, high quality data are of great importance for patient care. Due to the unique nature of this type of services, the purpose of this study was to assess data quality in emergency medical services using an objective approach. METHODS: This was a retrospective...

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Detalles Bibliográficos
Autores principales: Mashoufi, Mehrnaz, Ayatollahi, Haleh, Khorasani-Zavareh, Davoud, Talebi Azad Boni, Tahere
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885566/
https://www.ncbi.nlm.nih.gov/pubmed/36717771
http://dx.doi.org/10.1186/s12873-023-00781-2
Descripción
Sumario:BACKGROUND: In emergency medical services, high quality data are of great importance for patient care. Due to the unique nature of this type of services, the purpose of this study was to assess data quality in emergency medical services using an objective approach. METHODS: This was a retrospective quantitative study conducted in 2019. The research sample included the emergency medical records of patients who referred to three emergency departments by the pre-hospital emergency care services (n = 384). Initially a checklist was designed based on the data elements of the triage form, pre-hospital emergency care form, and emergency medical records. Then, data completeness, accuracy and timeliness were assessed. RESULTS: Data completeness in the triage form, pre-hospital emergency care form, and emergency medical records was 52.3%, 70% and 57.3%, respectively. Regarding data accuracy, most of the data elements were consistent. Measuring data timeliness showed that in some cases, paper-based ordering and computer-based data entry was not sequential. CONCLUSION: Data quality in emergency medical services was not satisfactory and there were some weaknesses in the documentation processes. The results of this study can inform the clinical and administrative staff to pay more attentions to these weaknesses and plan for data quality improvement.